Retinal image analysis: concepts, applications and potential

Patton, Niall; Aslam, Tariq; MacGillivray, Thomas J.; Deary, IJ; Dhillon, Baljean; Eikelboom, Robert H.; Yogesan, K.; Constable, Ian J.

doi:10.1016/j.ajo.2006.01.057

Cited by 105 publications

(147 citation statements)

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“…In many papers, a specificity value is also proposed with a sensitivity value. 3 We can decide whether a patient of a fundus image has diabetic retinopathy after finding how much hemorrhages are included in a fundus image. In this case, a sensitivity and a specificity can be proposed together.…”

Section: Resultsmentioning

confidence: 99%

“…The other is a bright lesion such as exudates and cotton wool spots. 3 This paper focuses on the detection of hemorrhages in diabetic retinopathy because the hemorrhage is one important diagnostic criterion to determine the severity of diabetic retinopathy. Currently, the diagnosis of DR is made manually by an ophthalmologist who detects and calculates the hemorrhage size.…”

Section: Introductionmentioning

confidence: 99%

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A Study on Hemorrhage Detection Using Hybrid Method in Fundus Images

et al. 2010

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Study on Hemorrhage Detection Using Hybrid Method in Fundus Images

et al. 2010

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“…These artefacts could be removed by changing the output threshold, as discussed previously. However, for a computer-aided DR screening program it is more important to correctly classify all patients with sight-threatening DR (high sensitivity), even if it is at the expense of misclassifying some healthy subjects in the DR group [5].…”

Section: Discussionmentioning

confidence: 99%

Neural network based detection of hard exudates in retinal images

García

Sánchez

López

et al. 2009

Computer Methods and Programs in Biomedicine

151

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“…More detailed definition of CRAE and CRVE can be found in [19]. AVR is calculated based on the calibers of all arterioles and venules passing through a concentric ring, which is defined as the range of 0.5-1.0 disc diameter (DD) [20] from the optic disc margin. DD is the diameter (about 2×1.5 mm across) of the optic nerve which is a circular to oval white area and centered at the retina.…”

Section: Avr Measurementmentioning

confidence: 99%

Retinal Vessel Detection and Measurement for Computer-aided Medical Diagnosis

Wee

2013

J Digit Imaging

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Since blood vessel detection and characteristic measurement for ocular retinal images is a fundamental problem in computer-aided medical diagnosis, automated algorithms/systems for vessel detection and measurement are always demanded. To support computer-aided diagnosis, an integrated approach/solution for vessel detection and diameter measurement is presented and validated. In the proposed approach, a Dempster-Shafer (D-S)-based edge detector is developed to obtain initial vessel edge information and an accurate vascular map for a retinal image. Then, the appropriate path and the centerline of a vessel of interest are identified automatically through graph search. Once the vessel path has been identified, the diameter of the vessel will be measured accordingly by the algorithm in real time. To achieve more accurate edge detection and diameter measurement, mixed Gaussian-matched filters are designed to refine the initial detection and measures. Other important medical indices of retinal vessels can also be calculated accordingly based on detection and measurement results. The efficiency of the proposed algorithm was validated by the retinal images obtained from different public databases. Experimental results show that the vessel detection rate of the algorithm is 100 % for large vessels and 89.9 % for small vessels, and the error rate on vessel diameter measurement is less than 5 %, which are all well within the acceptable range of deviation among the human graders.

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Retinal image analysis: concepts, applications and potential

Cited by 105 publications

References 0 publications

A Study on Hemorrhage Detection Using Hybrid Method in Fundus Images

A Study on Hemorrhage Detection Using Hybrid Method in Fundus Images

Neural network based detection of hard exudates in retinal images

Retinal Vessel Detection and Measurement for Computer-aided Medical Diagnosis

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